a. Background—calculating classroom needs that satisfy a certain course schedule can be a data analysis architects may not be trained to perform effectively, but it's integral to the space programming of an institutional building, which usually is a key service provided by an architect. Below are some methods of the trade, considered as prior arts.                i. Some deal with timetabling, but they tend to be over complicated and inaccessible to architects for their purpose. One example is covered in the research paper Solving the Teacher Assignment—Course Scheduling Problem by a Hybrid Algorithm. (see appendix A) Its authors seek to find a scheduling of the courses so they fit existing rooms. However in planning for new classroom buildings, there is already a set course schedule that is the best-yet product of student and faculty desires. The knowledge barrier to carry out the study described in the paper is beyond an architect's training. Also, considering the cultural and political constraints in setting class meeting times, architects need not shuffle the entire course schedule as a way to “optimize” it (timetabling). Architects, who are planning for new buildings, only need to find a set of rooms with sizes that can accommodate the majority of existing schedule, which has likely been tested by time.        ii. Another very popular method approaches classroom-planning with top-down parameters such as weekly contact hours. They offer an equivalent number of classrooms for a total number of students and their overall in-class hours. I consider these methods vague and “rule-of-thumb” in nature because they are based on the arithmetic average and a simple equation. Assignable square footage=station size x weekly student contact hours/average weekly room hours/utilization rate. See appendix B.        iii. Course schedules may have been visualized by architects such as this white paper by Sasaki (http://www.sasaki.com/blog/view/1077/). However, the method is used only in the context of understanding existing space conditions. No geometric computing (intersection of shapes or vectors) on the graph is executed to size future classrooms. The visualization is only used as diagnosis, not prognosis, as it states “ . . . visually displays existing course schedule information to easily understand the relationship . . . ”.        
b. There are some patents related to subject invention. However alone none of them can perform the task concerned.                i. A ray-box intersection patent lays foundation for API call. The patent concerns the performance of such computing and at the moment the method is available through many commercial software. U.S. Pat. No. 8,564,589B1        ii. A proposed method of matching resources is similar in process but in the embodiment context it will not find number of resources or number of “unmatched task” (class sessions in my case). US20110264482A1 (abandoned)        iii. A proposed patent for scheduling reservations at a facility is similar in matching preferences to spaces but it does not apply to embodiment case as it hinges upon already knowing the “client preferences” (room sizes). US20030005055A1 (abandoned)        iv. A patent for assigning teachers to students. This method has matching algorithm but is not suitable for space finding. This method assumes spaces are provided at fixed quantity. U.S. Pat. No. 8,170,465B2        v. A patent for visually arranging representations of physical documents is loosely similar to the idea of showing classes as boxes on computer screens. U.S. Pat. No. 4,601,003A        vi. A patent that make use of computer graphics to represent facility assets such as classrooms. However it does not provide quantitative analysis. U.S. Pat. No. 5,310,349A        vii. A patent that schedules classes given the educational resources. Helpful in starting a course schedule but least useful for determining classroom needs for a given course schedule. US20040009461A1, US20040115596A1        viii. A patent that schedules classes and optimizes the schedule. Not applicable to the embodiment case. Course schedule is a given and only manual intervention of a few sessions is appropriate. US20030065544A1        ix. Previous technologies in visualizing geometries are related, because the proposed method uses market software that embed those technologies. U.S. Pat. No. 8,042,056B2, U.S. Pat. No. 6,633,290B1        x. A patent that provide an architecture (computing) for data visualization but does not produce analytical results from geometry intersections on the visualizations. KR101555527B1        
c. Advantages of the proposed method of determining classroom needs are:                i. utilizing tools already familiar to architects (i.e. computer interface, common market software for 3d modeling etc.)        ii. analyzing course schedule data bottom-up, each class accounted for        iii. keeping course offering schedule intact at large, exposing pinch points when needed for review        iv. producing graphic representations that diagrams class fitting clearly        v. producing graphic representations that can be stylized by architect as instruments of professional service (e.g. drawings)        vi. producing results rapidly and automatically        